Wits School of Public Health

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Wits School of Public Health

Division of Epidemiology and Biostatistics

SHORT COURSES FOR 2016

Obtain Certificate of Competence in :

1. Processing, Distribution & Archiving I

2. Programming for Research Data Management I 3. Principles and Operations of Relational Databases 4. Implementation Science I

5. Introduction to Qualitative and Formative research mixed methods 6. Infectious (Communicable) Disease Epidemiology

7. Monitoring and Evaluation and Surveillance in Health 8. Health and Demographic Surveillance Database Systems 9. Data Management for Clinical Research Studies

10. Chronic (Non-Communicable) Disease Epidemiology 11. Clinical Trials

12. Statistical Consideration in Clinical Trials

13. Introduction to Data Management Systems, Structures and Models

INTRODUCTION

The Epidemiology and Biostatistics Division offers short courses in Infectious (Communicable) Disease Epidemiology, Chronic (Non-Communicable) Disease Epidemiology, Clinical Trials, and Statistical Consideration in Clinical Trials. The courses focus on the conduct of clinical trials and the detailed understanding of epidemiology of diseases in developing countries where resources are limited, coupled with statistical analyses of data collected during clinical trials.

The division also offers short courses in Introduction to Data Management Systems, Structures and Models, Principles and Operations of Relational Databases, Health and Demographic Surveillance Database Systems, Data Management for Clinical Research Studies, Data Processing, Distribution and Archiving I, Programming for Research Data Management I, Introduction to Qualitative and Formative research mixed methods, Implementation Science I and Monitoring, Evaluation and Surveillance in Health. The courses aim to give participants the requisite tools and skills to manage public health information systems as well as large longitudinal datasets. The short courses also expose

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data managers to statistical techniques that are typically used to analyze the data they manage. They also support the identification of health system bottlenecks and approaches to address them. These courses target health professionals who deal with health data management, analytics and health systems management.

1. Data Processing, Distribution and Archiving I

Date: March 14 - March 18, 2016. Time: 08h30-17h30 Each Day

About the Course

This course introduces the theory, principles and practice of programming for the purpose of developing applications to capture, store and manage data for public health research studies. Capturing and exploiting the inherent information contained within large research datasets poses a lot of statistical challenges. This course introduces the student to the fundamental programming techniques and algorithms needed to properly capture, store and manage these datasets. The course will focus on planning and organizing programs for information extraction from research data. Python, an open-source scripting language that allows rapid application development of both large and small software systems has been selected for this course. It is object-oriented by design and provides an excellent platform for learning the basics of language programming. The course will introduce the student to the features of Python that provides accessibility to databases, system administration and other useful services.

Application Deadline: March 01, 2016 Outsiders: R 6500

From Wits: R 3250

2. Programming for Research Data Management I

Date: March 28 - April 02, 2016. Time: 08h30-17h30 Each Day

This COURSE provides students with skills in the extraction reprocessing and storage of datasets. The module introduces the student to the Extraction, Transform and Load (ETL) process and data storage for both electronic and paper records. The course gives insight into industry standards in data documentation and data archival formats. Topics in module include Data extraction, transformation, loading (ETL) process, Analytical dataset production cycle, Data documentation: versioning, dataset citation, data fingerprinting, Using Data Documentation Initiative standards, Archival data formats, Data repositories, Paper and electronic data archiving.

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From Wits: R 3250

3. Principles and Operations of Relational Databases

Date:April 18 - April 22, 2016. Time: 08h30-17h30 Each Day

This module introduces the concept of Database design and use of database management systems to model and implement public health information systems. It includes extensive coverage of the relational model, relational algebra, and SQL, the standard language for creating, querying, and modifying relational and object-relational databases. It also covers XML data including DTDs and XML Schema for validation, and the query and transformation languages XPath, XQuery, and XSLT. The course includes database design in UML, and relational design principles based on dependencies and normal forms. The second component of this module places more emphasis on using these advance database programming techniques in the maintenance of large health-related data systems. The module equips the student with the skills of creating, maintaining, manipulating, updating, and retrieving information/data for analysis by statistical packages. Other topics covered in the second part of the module include transactions, authorization, integrity constraints and triggers, Database security, user authentication and recursion in SQL.

Application Deadline: April 04, 2016 Outsiders: R 6500

From Wits: R 3250

4. Implementation Science I

Date:April 11 - April 15, 2016. Time: 08h30-17h30 Each Day

This course has been developed to address the gap in implementation of proven interventions in the real world. There is abundant evidence of efficacy of interventions that have been carried out in Sub-Saharan Africa but these working interventions have not been backed up with knowledge and skills on how to deliver those interventions effectively in a real setting. Sub-Saharan Africa faces diverse challenges, including limited resources, poor socio-economic status and a broken health system. The course will provide skills in how these proven and affordable interventions can be implemented to improve health outcomes in the region. This requires tools, approaches that take into consideration evidence to enhance equity

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and efficiency in delivery of the services. Therefore the course will introduce participants to knowledge and skills to enable them to plan and carry out implementation research aimed at improving the implementation and management and control of disease and or conditions and other health programs.

From Wits: R 4000

5. Introduction to Qualitative and Formative research mixed methods

Date:July 11 - July 15, 2016. Time: 08h30-17h30 Each Day

Qualitative approaches provide insight, knowledge and perspectives about the evidence and the context in which implementation research is to occur. This course will introduce students to qualitative research methodology and different methodological approaches including: mixed methods, phenomenology, case studies, ethnography, grounded theory and narratives. Students will engage with both epistemology and ontology which underlies qualitative and quantitative research. The course provides both a theoretical and practical experience of some qualitative methods including observation, interviewing and focus groups. Students will learn a qualitative software package MAXQDA. Students are exposed to descriptive and comparative analysis as well as conceptualising and theorising from their data.

Application Deadline: June 27, 2016 Outsiders: R 8000

From Wits: R 4000

6. Infectious (Communicable) Disease Epidemiology

Date:July 18 - July 22, 2016. Time: 08h30-17h30 Each Day

This course will focus on the principles and practices of infectious disease epidemiology within an African context. On successful completion of the course, students will have a sound understanding of the principles of infectious disease epidemiology, a thorough knowledge of the epidemiology of key infectious diseases in Africa and an will be equipped with an approach to addressing infectious disease prevention and control. Content areas to be covered will include: measures of infectiousness, reproductive rates, herd immunity, vaccine efficacy, vaccine coverage, attack rates; epidemiology of HIV/AIDS, TB, malaria, diarrheal diseases and

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respiratory tract diseases; current issues in infectious diseases epidemiology and eradication of infectious diseases. A combination of formal lectures, group tutorials and practical exercises will be used.

Application Deadline: July 04, 2016 Outsiders: R 6500

From Wits: R 3250

7. Monitoring and Evaluation and Surveillance in Health

Date:August 08 - August 12, 2016. Time: 08h30-17h30 Each Day

This course provides students with the basic concepts and methodologies needed to undertake monitoring, evaluation, and surveillance of HIV/AIDS programs. The course covers data use, frameworks, program monitoring, indicators, information sources, evaluation designs, and surveillance. A particular focus is given to identifying what methods are needed for program monitoring, evaluation, and surveillance based on the implementation phase of the program (e.g., pilot testing a new strategy, evaluating the program outcomes, or implementing the program at scale). The focus of the course is on practical issues for undertaking program monitoring, evaluation and surveillance of HIV/AIDS programs.

From Wits: R 4000

8. Health and Demographic Surveillance Database Systems

This course builds on the concepts and techniques taught in the Principles and Operations of Relational Databases module. The course emphasis the planning, architecture, design, and implementation of massive-scale databases related to public health surveillance information systems. The appropriate design and management of such information systems is particularly useful for Health and Demography Surveillance Centers or Sites in developing countries. The course focuses on foundational concepts of distributed database theory including design and architecture, security, integrity, query processing and optimization, transaction management, concurrency control, and fault tolerance. These concepts are then applied to solve the complex interrelationships of local, national and regional

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independent but interrelated surveillance information systems and the constraints that legal restrictions create in the transfer and use of surveillance datasets.

From Wits: R 3250

9. Data Management for Clinical Research Studies

Date:August 29 - September 02, 2016. Time: 08h30-17h30 Each Day

This course introduces participants to the principles and skills required to collect and manage research data in a public health setting. We will evaluate different data collection tools and methods for various types of research studies. A major shortcoming in many countries is the absence of accurate data. The absence of accurate data makes it difficult to make evidence-based policy and planning decisions, monitor trends as well as monitor and evaluate interventions. The course introduces the concepts of proper database design and use of database management systems for public studies such as clinical trials in order to have consistent, secure, and efficient data collection.

Application Deadline: August 15, 2016 Outsiders: R 8000

From Wits: R 4000

10. Chronic (Non-Communicable) Disease Epidemiology

Chronic diseases are increasing in the developing world due to lifestyle changes associated with demographic, societal and epidemiologic transitions. This course provides an overview of the etiology, epidemiology, risk factors and public health importance of selected chronic diseases in developing countries. It addresses measurement issues in chronic disease epidemiology with respect to both exposure assessment and measurement of outcome along with practical considerations involved in conducting chronic disease epidemiology research. Major policy initiatives addressing globally the prevention and control of chronic diseases are presented.

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From Wits: R 3250

11. Clinical Trials

Date:August 29 - September 02, 2016. Time: 08h30-17h30 Each Day

The course provides an introduction to the area of clinical trials focusing on the conduct of clinical trials in developing countries where resources are limited. The main issues in the design, implementation and interpretation of clinical trials are introduced to students. In addition, the module (1) outlines the principles of comparative clinical trials in investigating safety, efficacy and effectiveness of treatments; (2) highlights strengths and weaknesses of clinical trial design in comparison to other study designs and (3) introduces the key elements and steps in clinical trial implementation, including calculation of sample sizes to provide adequate power to the trial. The key characteristics of clinical trials, which include ethical and methodological considerations, principles of clinical trial conduct, clinical trial organization and monitoring, data collection, data processing (data management), quality assurance and quality control, and trial reporting, will be comprehensively described. The roles of the data safety and monitoring committee (DSMB) and the community advisory board (CAB), as well as good clinical practice (GCP), are also highlighted.

From Wits: R 3250

12.

Statistical Consideration in Clinical Trials

Date:September 12 - September 16, 2016. Time: 08h30-17h30 Each Day

The demand for properly conducted clinical trials, providing a reliable and objective assessment of various treatments or drugs on patients, has increased over the years. Statistics has become an integral part of the design, data management and analysis of data arising from clinical trials. The proper use of statistics at all these stages is important for results to be acceptable to the wider community. It is apparent that there is need to match the growth in clinical trials by expansion of biostatistical expertise. The course is a combination of lectures and hands-on practical sessions. It aims to comprehensively discuss the statistical issues required to execute a clinical trial and to analyze data arising from such trials.

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From Wits: R 3250

13. Introduction to Data Management Systems, Structures and Models

Date:September 12 - September 16, 2015, 2016. Time: 08h30-17h30 Each Day

This course introduces to the student to more intermediate Structured Query Language (SQL) and develops on what they were introduced to in Principles and Operations of the Relational Databases. The course also introduces students to the concepts surrounding Demographic Surveillance Systems (DSS), DSS database design and structure as well as the basic relational model for DSS. Students are introduced to a sample DSS database (Agincourt 1in10) and are taught how to run basic queries to calculate basic demographic rates in various practical hands on sessions. At the conclusion of this module students will be able to understand and design a simple DSS longitudinal database as well as query and perform basic analyses on a standard relational DSS database.

From Wits: R 3250

Wits School of Public Health